Course coordinator
Associate Professor Cheong Xin Chan
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Chemistry & Molec Biosciences
This course aims to provide students from a broad range of backgrounds with an introduction to bioinformatics, an emerging discipline that is transforming how we make discoveries in molecular bioscience. The course develops both theoretical and practical skills in bioinformatics, with an emphasis on the extraction and analysis of data, driven by current technologies. The course aims to equip students with a working knowledge of computing methodology relevant to the biosciences, including the use of databases, the automation of
common bioinformatics tools, and the development of methods tailored for representative problems and data types in molecular biosciences. The course will prepare students for more advanced courses in the area of bioinformatics, genomics and systems biology.
Bioinformatics is the field that uses computational and mathematical approaches to solve biological problems. It is transforming how we approach scientific problems, and enabling us to tackle larger and more complex challenges in life sciences. This course is your gateway to the exciting world of bioinformatics and computational biology.
With advances in genome sequencing and high-throughput biotechnologies, vast amounts of biological data are generated every day, far exceeding our capacity to analyse or synthesise knowledge from them. In addition, existing tools quickly become outdated, creating a demand for new bioinformatics methods.
This course will teach you how to leverage computational tools to uncover patterns in these data and transform them into meaningful biological insights, and address emerging challenges in this rapidly evolving field. The curriculum begins with a brief foundational introduction to molecular biology and dives into key topics, including:
(a) comparing molecular sequences to uncover their biological importance;
(b) analysing high-throughput data to study gene expression and genome sequences;
(c) understanding evolutionary relationships using phylogenetics;
(d) understanding biological datatypes, databases, and their applications; and
(e) predicting protein structures and their functions.
Throughout, the course instils and nurtures computational thinking and skillsets to support the analysis of large-scale datasets (i.e. big-data analysis).
This course includes two streams of assessments: one for bioinformatics "users" and another for bioinformatics "developers." The "user" stream focuses on biological problems, while the "developer" stream emphasises computational challenges. Students enrolled in postgraduate Bioinformatics programs (such as the Master of Bioinformatics), are required to complete the "developer" stream. Students from other programs may request to choose a stream, but final placement will be determined individually after an evaluation process.
By the end of this course, you will have a strong understanding of how bioinformatics is used to answer fundamental biological questions in fields such as medicine, biotechnology, and environmental science.
The demand for bioinformatics professionals is strong and growing across diverse industries, including healthcare, agriculture, biotechnology, pharmaceuticals, and environmental management. Graduates equipped with bioinformatic skills are particularly sought after in the areas of drug design and patent management, gene therapy, crops and livestock breeding (and farming), aquaculture, and environmental management, for their ability to translate biological data into practical optimised solutions.
If you are passionate about using data to drive breakthroughs in biology, this course is the perfect starting point for your journey.
Course requirements
Assumed background
The course suits both biological scientists who want to bridge wet and dry labs, and computing and maths students who would like to solve real scientific problems.
Biology is not required for this course, but we will assume an interest and a keen attitude. The necessary concepts from molecular biology are introduced as part of the first section of the course. This course is designed to complement BINF6001 by introducing the biology and computing skillset necessary for more advanced studies in bioinformatics.
The course does not assume exposure to programming, but an analytical and computer-savvy mindset is helpful. The necessary concepts and technical skills are introduced as part of the first section of the course. CSSE7030 runs in parallel with this course and students are recommended to complete this in preparation for advanced studies in bioinformatics.
Companion or co-requisite courses
You'll need to complete the following courses at the same time:
BINF6001
Recommended companion or co-requisite courses
We recommend completing the following courses at the same time:
CSSE7030
Course contact
Course staff
Lecturer
Associate Professor Cheong Xin Chan
Associate Professor Scott Beatson
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Please check your timetable regularly.
Aims and outcomes
This course offers both theoretical knowledge and practical experience, preparing you to understand, analyse, and solve real-world bioinformatic problems effectively.
It is designed to enable you to:
- Build foundational skills in bioinformatics: Develop a strong understanding of molecular biology and biochemistry, and the practical skills in analytical thinking to solve scientific problems. Learn key aspects of molecular biology and computing relevant to bioinformatics, gain programming experience, work with biological data, and critically evaluate bioinformatic approaches to scientific problems.
- Understand the scope of bioinformatics: Explore how computational and mathematical approaches are applied to biological sciences, both as a user of bioinformatic tools and as a developer. Understand the field's definition, the problems it addresses, the datasets and technologies it uses, and the theoretical and computational frameworks that underpin it.
- Understand the context of bioinformatic applications: Discover how different bioinformatics methods address scientific problems, and identify which problems can be realistically addressed. Topics include sequence analysis, phylogenetics, gene expression, structural bioinformatics, genomics, and databases.
- Consolidate knowledge of biology in the bioinformatic context: Acquire a solid understanding of molecular biology and biochemistry to contextualise bioinformatic problems. Learn about biological sequences (DNA, RNA, and proteins), their structure, basic chemistry, and expression, connect biological challenges with appropriate computational methods and data structures.
- Recognise diversity of bioinformatic problems: Develop practical and intuitive skills to identify suitable bioinformatic approaches (such as gene ontology, sequence alignment, phylogenetics, and protein-structure prediction) based on the problem at hand.
- Understand the potentia
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Understand key concepts of molecular biology and sequences, and how bioinformatics and publicly available data contribute to biological discovery.
LO2.
Analyse DNA, RNA, and protein sequences, identify patterns, and compare them to generate biological insights.
LO3.
Understand the principles of phylogenetics and its application to study evolutionary changes in sequences.
LO4.
Explain key technologies for generating biological data and understand the different types and formats of these data.
LO5.
Use bioinformatic tools including Python programming to solve biological problems, including working with biological databases and/or developing/refining methods.
LO6.
Understand key computing concepts in bioinformatics and the challenges involved in analysing complex biological data.
LO7.
Identify research areas and career opportunities in bioinformatics across academia and industry.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Quiz |
Online Quiz (Assessment 1)
|
15% |
21/03/2025 2:00 pm |
| Paper/ Report/ Annotation, Tutorial/ Problem Set |
Workshop Assessment (Assessment 2)
|
20% Workshop 1 is a Pass/Fail. Workshop 2 has a 20% weighting of overall course marks. |
Workshop 1 (Pass/Fail) 4/04/2025 2:00 pm Workshop 2 (20%) 2/05/2025 2:00 pm |
| Paper/ Report/ Annotation, Performance, Presentation, Project, Tutorial/ Problem Set |
Group Project (Assessment 3)
|
25% |
30/05/2025 2:00 pm |
| Examination |
End-of-Semester Exam
|
40% |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Online Quiz (Assessment 1)
- Hurdle
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 15%
- Due date
21/03/2025 2:00 pm
- Learning outcomes
- L01, L02, L03, L05
Task description
Assessment 1 is an Online Quiz that consists of multiple-choice questions. It assesses the students understanding of the Core Practicals.
Estimated time to complete this quiz is 30-45 minutes.
Use of Artificial Intelligence (AI) and Machine Translation (MT)
This task has been designed to be challenging, authentic and complex. Whilst students may use AI technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.
Hurdle requirements
See ADDITIONAL COURSE GRADING INFORMATION for the hurdle/s relating to this assessment item.Submission guidelines
To be submitted on Blackboard
Deferral or extension
You may be able to apply for an extension.
Applications for Extensions
Information on applying for an extension can be found here: my.UQ Applying for an extension.
Extension applications must be received by the assessment due date and time.
If you are unable to provide approved documentation to support your application by the due date and time, you must still submit your application by the deadline but with an attached Word document that outlines why you cannot provide the approved documentation by the deadline. You will then need to acquire and upload the approved documentation to your request within 24 hours. Please note: When an extension request has been submitted and is pending, students are expected to continue to work on the assessment item, with the aim of submitting by the requested due date and time.
Prolonged Absence
If you have been ill or unable to attend class for more than 14 days, we advise you to carefully consider whether you are capable of successfully completing your courses this semester.
Extensions with Student Access Plans (SAP)
For extensions up to 7 days, your SAP is all that is required as documentation to support your application. However, extension requests longer than 7 days (for any one assessment item) will require the submission of additional supporting documentation e.g. a medical certificate.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 10% will be deducted per day for up to 7 calendar days, at which point your submission will receive a mark of zero (0) unless an extension has been approved.
In most instances one or more hurdles will apply to your assessment item so you will need to submit it to fulfil the requirements of the course regardless of how late it is and the mark you are likely to be awarded.
Workshop Assessment (Assessment 2)
- Hurdle
- Mode
- Written
- Category
- Paper/ Report/ Annotation, Tutorial/ Problem Set
- Weight
- 20% Workshop 1 is a Pass/Fail. Workshop 2 has a 20% weighting of overall course marks.
- Due date
Workshop 1 (Pass/Fail) 4/04/2025 2:00 pm
Workshop 2 (20%) 2/05/2025 2:00 pm
- Learning outcomes
- L01, L02, L03, L05, L06
Task description
This Assessment consists of two workshops running in two streams: (a) user stream (with a stronger biology component), and (b) developer stream (with a stronger informatics component). Students will be assigned to a stream prior to the beginning of this assessment, and expected to remain in the assigned stream for both workshops.
Workshop 1 will be held during scheduled practical sessions in Weeks 5-6. This workshop is designed to assess students’ fundamental understanding in the practical aspects in performing routine bioinformatic tasks relevant to omics data analysis. Students are expected to (1) work through a set of computer-based tasks and (2) submit short-answers to a set of designated questions. A successful attempt (i.e. submitted answers to all questions) by the specified due date is considered "pass".
Workshop 2 will be held during scheduled practical sessions in Weeks 7-9. This workshop will be structured around completing exercises in sequence analysis and phylogenetics. This workshop will introduce students to resources (e.g., databases, data sources, literature), tools (e.g., sequence database search tools, statistical tests) and methods (e.g. inferring phylogenetic relationships) used to address components of a biological problem.
More detail will be available on Blackboard.
Use of Artificial Intelligence (AI) and Machine Translation (MT)
This task has been designed to be challenging, authentic and complex. Whilst students may use AI technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.
Hurdle requirements
See ADDITIONAL COURSE GRADING INFORMATION for the hurdle/s relating to this assessment item.Submission guidelines
To be submitted on Blackboard
Deferral or extension
You may be able to apply for an extension.
Applications for Extensions
Information on applying for an extension can be found here: my.UQ Applying for an extension.
Extension applications must be received by the assessment due date and time.
If you are unable to provide approved documentation to support your application by the due date and time, you must still submit your application by the deadline but with an attached Word document that outlines why you cannot provide the approved documentation by the deadline. You will then need to acquire and upload the approved documentation to your request within 24 hours. Please note: When an extension request has been submitted and is pending, students are expected to continue to work on the assessment item, with the aim of submitting by the requested due date and time.
Prolonged Absence
If you have been ill or unable to attend class for more than 14 days, we advise you to carefully consider whether you are capable of successfully completing your courses this semester.
Extensions with Student Access Plans (SAP)
For extensions up to 7 days, your SAP is all that is required as documentation to support your application. However, extension requests longer than 7 days (for any one assessment item) will require the submission of additional supporting documentation e.g. a medical certificate.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 10% will be deducted per day for up to 7 calendar days, at which point your submission will receive a mark of zero (0) unless an extension has been approved.
In most instances one or more hurdles will apply to your assessment item so you will need to submit it to fulfil the requirements of the course regardless of how late it is and the mark you are likely to be awarded.
Group Project (Assessment 3)
- Hurdle
- Team or group-based
- In-person
- Mode
- Activity/ Performance, Product/ Artefact/ Multimedia, Written
- Category
- Paper/ Report/ Annotation, Performance, Presentation, Project, Tutorial/ Problem Set
- Weight
- 25%
- Due date
30/05/2025 2:00 pm
- Other conditions
- Peer assessment factor.
- Learning outcomes
- L02, L03, L04, L05, L06
Task description
Assessment 3 is a Group Project presentation of research findings, based on the tasks outlined in the project assignment, in omics data analysis. Students will work in groups of 5-6. Each group will consist at least one member from the developer stream (in the earlier Workshops). Contact sessions will be run as interactive classes, and requires active participation. There are three components in this Assessment:
(a) Video presentation: submitted through Blackboard, during which each student in a group is required to present in turn within an allocated time.
(b) Interview: each group will attend an in-person interview with the assessors who will pose questions related to the high-level concepts, rationale and execution of the project.
(c) Peer assessment: each member will assess their peers within the group, based on their capacity as a team player and leader, and their research performance.
The activities in this Assessment emulate a real-life workplace scenario in a bioinformatics-relevant industry. More detail will be available on Blackboard.
Use of Artificial Intelligence (AI) and Machine Translation (MT)
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
See ADDITIONAL COURSE GRADING INFORMATION for the hurdle/s relating to this assessment item.Submission guidelines
To be submitted on Blackboard
Deferral or extension
You may be able to apply for an extension.
Applications for Extensions
Information on applying for an extension can be found here: my.UQ Applying for an extension.
Extension applications must be received by the assessment due date and time.
If you are unable to provide approved documentation to support your application by the due date and time, you must still submit your application by the deadline but with an attached Word document that outlines why you cannot provide the approved documentation by the deadline. You will then need to acquire and upload the approved documentation to your request within 24 hours. Please note: When an extension request has been submitted and is pending, students are expected to continue to work on the assessment item, with the aim of submitting by the requested due date and time.
Prolonged Absence
If you have been ill or unable to attend class for more than 14 days, we advise you to carefully consider whether you are capable of successfully completing your courses this semester.
Extensions with Student Access Plans (SAP)
For extensions up to 7 days, your SAP is all that is required as documentation to support your application. However, extension requests longer than 7 days (for any one assessment item) will require the submission of additional supporting documentation e.g. a medical certificate.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 10% will be deducted per day for up to 7 calendar days, at which point your submission will receive a mark of zero (0) unless an extension has been approved.
In most instances one or more hurdles will apply to your assessment item so you will need to submit it to fulfil the requirements of the course regardless of how late it is and the mark you are likely to be awarded.
End-of-Semester Exam
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Learning outcomes
- L01, L03, L04, L06
Task description
This assessment aims to test the breadth of the student's knowledge in bioinformatics. Particular emphasis is put on knowledge that is not explicitly assessed by means of assignments and practicals. The student will be given a set of short-answer questions and problems, covering the major topics discussed in the lectorials. Further details will be provided on Blackboard.
Use of Artificial Intelligence (AI) and Machine Translation (MT)
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See ADDITIONAL COURSE GRADING INFORMATION for the hurdle/s relating to this assessment item.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | Any calculator permitted |
| Open/closed book | Closed Book examination - no written materials permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: A student will earn a grade of 1 if they submit some assessable material but they show a poor knowledge of the basic concepts in the course material. This includes attempts at answering some questions but showing an extremely poor understanding of the key concepts. The minimum percentage required for this grade is: 0% |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: To earn a grade of 2, a student must demonstrate some knowledge of the basic concepts in the course material. This includes attempts at expressing their deductions and explanations and attempts to answer a few questions accurately. The minimum percentage required for this grade is: 30% |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: To earn a grade of 3, a student must demonstrate some knowledge of the basic concepts in the course material. This includes occasional expression of their deductions and explanations, the use of a few appropriate and efficient bioinformatics techniques and attempts to answer a few questions and tasks accurately and with appropriate justification. They will have demonstrated knowledge of techniques used to solve problems. The minimum percentage required for this grade is: 45% |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: To earn a grade of 4, a student must demonstrate an understanding of the basic concepts in the course material. This includes occasionally expressing their deductions and explanations clearly, the occasional use of appropriate and efficient bioinformatics techniques and accurate answers to a few questions and tasks with appropriate justification. They will have demonstrated knowledge of techniques used to solve problems and applied this knowledge in some cases. The minimum percentage required for this grade is: 50% |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: To earn a grade of 5, a student must demonstrate an adequate understanding of the course material as whole (the final examination must be passed to earn this grade or higher). This includes clear expression of some of their deductions and explanations, the use of appropriate and efficient bioinformatics techniques in some situations and accurate answers to some questions and tasks with appropriate justification. They will be able to apply these techniques to solve fundamental problems. The minimum percentage required for this grade is: 65% |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: To earn a grade of 6, a student must demonstrate a comprehensive understanding of the course material. This includes clear expression of most of their deductions and explanations, the general use of appropriate and efficient bioinformatics techniques and accurate answers to most questions and tasks with appropriate justification. They will be able to apply these techniques to partially solve both theoretical and practical problems. The minimum percentage required for this grade is: 75% |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: To earn a grade of 7, a student must demonstrate an excellent understanding of the course material. This includes clear expression of nearly all their deductions and explanations, the use of appropriate and efficient bioinformatics techniques and accurate answers to nearly all questions and tasks with appropriate justification. They will be able to apply bioinformatics techniques to completely solve both theoretical and practical problems. The minimum percentage required for this grade is: 85% |
Additional course grading information
Assessment Hurdles
In order to pass this course, you must meet ALL of the following requirements (if you do not meet these requirements, the maximum grade you will receive will be a 3):
- You must obtain an overall course mark of 50% or more; and
- You must obtain an overall mark of 40% or more on the end of semester exam; and
- You must obtain a minimum weighted average mark of 40% across all other non-examination course assessment items.
Supplementary assessment
Supplementary assessment is available for this course.
Should you fail a course with a grade of 3, you may be eligible for supplementary assessment. Refer to my.UQ for information on supplementary assessment and how to apply.
Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.
If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met.
Supplementary assessment can take any form (such as a written report, oral presentation, examination or other appropriate assessment) and may test specific learning outcomes tailored to the individual student, or all learning outcomes.
To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment.
Additional assessment information
Assessment Submission
It is the responsibility of the student to ensure the on time, correct and complete submission of all assessment items.
Students are responsible for retaining evidence of submission by the due date for all assessment items, in the required form (for example, screenshot, email, photo, and an unaltered copy of submitted work).
In the case of a Blackboard outage, contact the Course Coordinator as soon as possible to confirm the outage with ITS.
Assessment/Attendance
Notify your Course Coordinator as soon as you become aware of any issue that may affect your ability to meet the assessment/attendance requirements of the course. The my.UQ website and the Course Profile (CP) for your course provide information about your course requirements, the rules associated with your courses and services offered by the University.
A note for repeating students in this course
Only learning activities and/or assessment items completed during the study period of enrolment, including any approved extensions, may contribute to your grade in this course. The whole or partial use of assessment items previously submitted for the same course, for a course at any institution, or for published material, is not permitted without written permission of the Course Coordinator.
Important Note
Turnitin is to be used for assignments/laboratory reports to check for plagiarism. Penalties can be severe for plagiarism.
The University has adopted the following definition of plagiarism: Plagiarism is the act of misrepresenting as one's own original work the ideas, interpretations, words or creative works of another either intentionally or unintentionally. These include published and unpublished documents, designs, music, sounds, images, photographs, computer codes and ideas gained through working in a group. These ideas, interpretations, words or works may be found in print and/or electronic media.
Students should read the UQ Student Integrity and Misconduct Policy.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
Blackboard
Supplementary material will be posted on the Blackboard site for the course at learn.uq.edu.au.
Please check the Announcements section of the Blackboard site regularly for information updates. The site contains essential information associated with this course. Specifically, you will find lecture notes, additional reading material and workshop specifications.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 2 |
Lecture |
Introduction to molecular biology Introduction to the course and molecular biology Learning outcomes: L01 |
Practical |
Core Practicals Core bioinformatics practicals on the use of public databases and analysis of biological sequences Learning outcomes: L01, L02, L03, L05 |
|
Multiple weeks From Week 3 To Week 4 |
Tutorial |
Introduction to bioinformatics computing Introduction to Galaxy, UNIX commandline, and simple scripting in Python Learning outcomes: L05, L06 |
Multiple weeks From Week 3 To Week 5 |
Lecture |
Sequence analysis Sequence analysis in bioinformatics (conservation, sequence alignment, high-throughput sequences, profiles, motifs) Learning outcomes: L01, L02 |
Multiple weeks From Week 5 To Week 6 |
Workshop |
Workshop 1: Genome and RNAseq/ChIPseq analysis 1A (user stream; RNAseq) or 1B (developer stream; ChIPseq). Design and implementation of computational workflows for bioinformatic analysis. This is a Course Assessment Hurdle. See ADDITIONAL COURSE GRADING INFORMATION for the hurdle/s relating to this assessment item. Learning outcomes: L01, L02, L05, L06 |
Multiple weeks From Week 6 To Week 7 |
Lecture |
Phylogenetics Phylogenetic methods in bioinformatics Learning outcomes: L03 |
Multiple weeks From Week 7 To Week 9 |
Workshop |
Workshop 2: Sequence analysis and phylogenetics 2A (user stream) or 2B (developer stream) Learning outcomes: L02, L03, L05, L06 |
Week 8 (14 Apr - 20 Apr) |
Lecture |
Gene expression analysis Bioinformatic analysis of gene expression and transcriptome data Learning outcomes: L02, L04 |
Week 9 (28 Apr - 04 May) |
Lecture |
Databases Biological databases and ontology Learning outcomes: L05, L06 |
Multiple weeks From Week 10 To Week 13 |
Workshop |
Group Project: Omics data analysis Group research project on genome-scale data analysis, guided with practical material and exercises. Learning outcomes: L02, L03, L04, L05, L06 |
Week 11 (12 May - 18 May) |
Lecture |
Protein bioinformatics Learning outcomes: L05, L06 |
Week 12 (19 May - 25 May) |
Workshop |
Career Panel Forum Open discussion forum about career prospects in bioinformatics Learning outcomes: L07 |
Week 13 (26 May - 01 Jun) |
Lecture |
Review Review of course content and preparation for the End-of-Semester Exam Learning outcomes: L01, L03, L04, L06 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.